Post on 18-Jan-2016
transcript
Threshold Modelsof Technological Transitions
Utrecht UniversitySummerschool Complex Systems
August 2015
Introduction• A large part of complexity research deals with conditions under which autonomous
particles or agents suddenly show coordinated behaviour leading to the emergence of macroscopic patterns.
• In the social sciences this is an old question as human agents are in principle driven by personal contexts, yet sometimes show remarkable coordinated behaviour. Think of social unrest, social norms, fashions, media hypes, etc.
• The threshold is generally expressed as the number of other agents already adopting. Hence, many technologies are slow to diffuse due to this coordination, a.k.a. lock-in problem.
• There is a wide interest because of the need of sustainability transitions. • The take away message holds that there are many different but related ways to
explain sudden transitions, which means that empirical research really has to go to the micro level to understand mechanism or mechanisms.
• Similarly, policy will only work well if the exact process underlying technology adoption is well understood.
Structure• I will discuss:
– The classic lock-in model of competing technologies– The modified lock-in model of transitions– Informational cascades– The NK-model– Percolation model
• Background literature:
The example of cars, bikes and planes
PAGE 430/09/09
And the dominant designs that followed
PAGE 530/09/09
A more recent example …
PAGE 630/09/09
Dominant design
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Lock-in
• Path dependence
• Irreversibility
• Multiple equilibria
• Unpredictability
• Population consists of 50-50 distribution of R-agents and S-agents
• Sequential decision-making
Modified lock-in model of technological transitions
Modified lock-in model
Lock-in model
Informational cascades
NK-model
NK-model
NK-model
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Percolation in a social network
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Percolation in a social network
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Different network structures
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• Upper bound to diffusion: 45º line (perfect information)
• Phase changes: from a non-diffusion to a diffusion regime
• Regular and Small world networks very inefficient
Thresholds depend on network structrures
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Thresholds depend on network structrures